Accelerate
Day-to-Day Cloud Operations with Torque’s AI Copilot
Quali Torque’s AI Copilot handles the heavy lifting so your teams can deliver and optimize cloud infrastructure faster and more efficiently.
Stop Wasting Time on
Manual Cloud Operations
Let Torque’s AI Copilot handle the day-to-day tasks needed to deliver and optimize your cloud infrastructure.
Design & Coding
Submit AI prompts to automate the design and generation of code for your unique cloud workloads.
Investigating Errors
Review AI-generated insights into the root causes behind provisioning errors, configuration drift, and other issues.
Optimizing Cloud Costs
Eliminate wasted costs with AI-generated insights into idle resources that inflate the cloud bill.
See How Torque’s AI Copilot Accelerates Productivity
See how to simplify the creation, management, and optimization of cloud environments using Torque’s AI Copilot.
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Torque’s AI Copilot Accelerates DevOps & Platform Engineering
Environment Orchestration & Design
Torque connects to your repositories to leverage your IaC and other resources as components in environments. Using Torque’s AI Copilot, users can submit natural-language AI prompts to automate the design and creation of code defining all the infrastructure, applications, and other services needed to generate an output. This Environment as Code blueprint can be provisioned repeatedly and maintained continuously, providing a foundation for efficient cloud management.
Diagnosing IaC Errors
Since Torque monitors the provisioning and state of each component in an environment, the platform can recognize when errors occur. Torque’s AI Copilot provides insights into the root causes of errors so engineers can quickly reconcile them without digging through code.
Creating Governance Policies & Workflows
Torque’s AI Copilot can create additional code to help with the governance and management of your cloud infrastructure, helping to reduce the learning curve to adopt standards like Open Policy Agent while also accelerating the creation of workflows that can streamline Day 2 operations.
Identifying Wasted Cloud Costs
Torque’s AI Copilot monitors the capacity of all cloud resources deployed in support of your environments, flags those that are not being actively used, and calculates the potential cost savings from terminating them. This provides engineering and FinOps teams insights into cloud cost savings opportunities, as well as the context to understand who may be responsible for provisioning these idle resources.
On-Demand Support
As a persistent feature throughout the Torque user experience, the AI Copilot can answer any question that users may have about managing their infrastructure, providing an on-demand resource to help work through any issue that could hold back performance, productivity, and efficiency.
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Frequently Asked Questions
Torque connects to the user’s repositories, discovers the resources within them (with support for Terraform, OpenTofu, Ansible, CloudFormation, Helm, Kubernetes, and other tools), and creates normalized versions of each resource within Torque. This normalization eliminates discrepancies between each tool so the resources they define can be configured to work together easily.
To support an environment, Torque pulls the code from each resource needed into a new file, which includes the definitions of dependencies, input parameters, and any other details needed to generate the environment output. This code, referred to as an Environment as Code blueprint, can be provisioned repeatedly and maintained continuously.
Torque’s AI Copilot was created to accelerate this process by responding to user-submitted prompts. This eliminates the manual configuration of code so more users can create more Environment as Code blueprints faster.
Any resource deployed via Torque is treated as a managed, stateful environment.
This can be as simple as a basic virtual machine or as complex as a production environment supporting an AI Agent or software application. Common use cases include environments for software development, testing, demos, training, and onboarding. Some of our users have leveraged Torque to manage each layer of the AI tech stack as well.
Torque manages these workloads in a way that goes beyond just provisioning code. By monitoring the resources deployed, Torque can recognize when configurations drift or errors occur; automate the lifecycle for individual resources within the environment; automate routine Day 2 actions; enforce custom policies; and provide visibility into the activity and associated cloud costs for any resource.
Torque’s AI Copilot was created to handle some of the activity that can have a significant impact on the delivery, maintenance, and cost efficiency of these environments. This enables more of our customers to better manage their cloud activity while also improving internal productivity.
Once Torque provisions an environment, the platform also monitors the state of all resources and configurations within that environment. This enables the platform to identify when a cloud service or application failed to provision correctly.
Torque’s AI Copilot is trained on the intricacies of cloud infrastructure provisioning, which enables the tool to provide insights into the potential causes of an error. This information can help engineers correct errors more quickly.
Idle cloud resources are among the most common sources of wasted cloud costs. Since Torque monitors the state of all cloud resources deployed via the platform, it can also monitor how that infrastructure is used.
Torque’s AI Copilot monitors all actively deployed resources in the user’s account and identifies those with unused capacity. Then, based on the resource, instance size, and environment runtime (which is also set in advance via Torque), Torque’s AI Copilot calculates the cost of that environment over the lifecycle of that deployment.
Torque’s Inactivity report aggregates these opportunities and provides context to understand what resource was provisioned, what environment it supports, and the user who provisioned it. This equips FinOps and engineering teams with insights to eliminate wasted cloud costs without disrupting infrastructure that their teams need.
